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The GlobThe Global White Biotechnology Market 2025-2035

Best Price Guarantee Length Publisher Published Date SKU
from $1,500 585 Pages Future Markets, Inc. May, 2025 FTMK20037854
Best Price Guarantee
Price from $1,500
Length 585 Pages
Publisher Future Markets, Inc.
Published Date May, 2025
SKU FTMK20037854

The global white (industrial) biotechnology market is experiencing significant growth, driven by increasing demand for sustainable alternatives to traditional petroleum-based products. White biotechnology leverages biological systems, enzymes, and microorganisms to produce chemicals, materials, and energy through environmentally friendly processes. With rising environmental concerns, government regulations supporting bio-based products, and technological advancements in synthetic biology, the sector is poised for substantial expansion. The market is characterized by diverse applications across multiple industries including biofuels, bio-based chemicals, bioplastics, pharmaceuticals, food ingredients, textiles, and construction materials. Major growth drivers include carbon taxation policies, increasing consumer preference for sustainable products, and corporate sustainability commitments. The transition toward circular economy principles is further accelerating adoption as white biotechnology enables the valorization of various waste streams including agricultural residues, forestry waste, municipal solid waste, and industrial by-products.

Technological innovations in synthetic biology, metabolic engineering, and the emerging field of generative biology are dramatically improving production efficiencies and expanding the range of possible bio-manufactured molecules. Advanced fermentation processes, cell-free systems, and the development of novel microbial chassis organisms are contributing to increased commercial viability of white biotechnology products.

Report Contents include:
Market Analysis and Forecasts 2025-2035
Global market revenues by molecule type
Market segmentation by application sector
Regional market analysis and growth projections
Competitive landscape and key player positioning
Technology Landscape Assessment
Production hosts (bacteria, yeast, fungi, marine organisms)
Biomanufacturing processes and optimization techniques
Synthetic biology advancements and applications
Generative biology approaches and impact
Feedstock analysis and alternative resource utilization
Application Sector Analysis
Biofuels (bioethanol, biodiesel, biogas, biojet fuel)
Bio-based chemicals (organic acids, alcohols, monomers)
Bioplastics and biopolymers (PLA, PHAs, bio-PET)
Food and nutraceutical ingredients
Agricultural biotechnology
Textile applications
Pharmaceuticals and cosmetics
Construction materials
Sustainability and Circular Economy Integration
White biotechnology for waste valorization
Carbon capture utilization
Industrial symbiosis opportunities
Environmental impact assessment
Strategic Insights and Opportunities
Technology adoption trends
Regulatory landscape analysis
Investment patterns and funding environment
Strategic recommendations for market participants
Comprehensive Company Profiles
Detailed analysis of 395+ market participants
Technology platforms and proprietary processes
Commercial deployments and capacity expansions
Partnership and collaboration networks

The report provides comprehensive profiles of over 395 companies operating across the industrial biotechnology value chain. These include established industry leaders like Novozymes, Braskem, LanzaTech, and Corbion, alongside innovative startups developing novel technologies and applications. The diverse ecosystem encompasses specialized synthetic biology platforms (Ginkgo Bioworks, Arzeda), biofuel producers (Aemetis, Gevo), bioplastics manufacturers (NatureWorks, Total Energies Corbion, Danimer Scientific), bio-based chemical developers (Avantium, METEX), cell-free system innovators (EnginZyme, Solugen), and companies focused on emerging applications like biocement (Biomason) and bio-textiles (Bolt Threads, Modern Meadow, Spiber). The landscape also includes AI-driven biotechnology platforms (Asimov, Zymergen) and specialized waste-to-value companies (Celtic Renewables, Full Cycle Bioplastics). This comprehensive company analysis provides unparalleled insights into the competitive dynamics, technological capabilities, and strategic positioning of key market participants across the global industrial biotechnology ecosystem.


1 EXECUTIVE SUMMARY
1.1 Biotechnology "colours"
1.2 Definition
1.3 Comparison with conventional processes
1.4 Markets and applications
1.5 Advantages
1.6 Sustainability
1.7 White Biotechnology for the Circular Economy
1.7.1 Agricultural Waste
1.7.2 Forestry and Paper Waste
1.7.3 Gas Fermentation
1.7.4 Plastics Upcycling
1.7.5 Wastewater Valorization
2 TECHNOLOGY ANALYSIS
2.1 Production hosts
2.1.1 Bacteria
2.1.2 Yeast
2.1.3 Fungi
2.1.4 Marine
2.1.5 Enzymes
2.1.6 Photosynthetic organisms
2.2 Biomanufacturing processes
2.2.1 Batch biomanufacturing
2.2.2 Continuous biomanufacturing
2.2.3 Cell factories for biomanufacturing
2.2.4 Industry-Specific Microorganism Applications
2.2.4.1 Escherichia coli (E. coli)
2.2.4.2 Corynebacterium glutamicum (C. glutamicum)
2.2.4.3 Bacillus subtilis (B. subtilis)
2.2.4.4 Saccharomyces cerevisiae (S. cerevisiae)
2.2.4.5 Yarrowia lipolytica (Y. lipolytica)
2.2.5 Machine learning
2.2.6 Downstream processing
2.2.7 Perfusion bioreactors
2.2.8 Tangential flow filtration (TFF)
2.2.9 Hybrid biotechnological-chemical approaches
2.2.10 Process intensification and high-cell-density fermentation
2.3 Synthetic Biology
2.3.1 Technology Overview
2.3.2 Synthetic biology applied to white biotechnology
2.3.3 Metabolic engineering
2.3.3.1 DNA synthesis
2.3.3.2 CRISPR
2.3.3.2.1 CRISPR/Cas9-modified biosynthetic pathways
2.3.4 Protein/Enzyme Engineering
2.3.4.1 Computer-aided Design
2.3.4.2 Synthetic Biology and Metabolic Engineering (200 words)
2.3.4.3 Industrial Microbial Strains
2.3.4.4 Scaling
2.3.5 Strain construction and optimization
2.3.6 Smart bioprocessing
2.3.7 Cell-free systems
2.3.8 Chassis organisms
2.3.9 Biomimetics
2.3.10 Sustainable materials
2.3.11 Robotics and automation
2.3.11.1 Robotic cloud laboratories
2.3.11.2 Automating organism design
2.3.11.3 Artificial intelligence and machine learning
2.3.11.4 Automating Organism Design
2.3.11.5 De Novo Protein Prediction
2.3.11.6 Companies
2.3.12 Fermentation Processes
2.4 Generative Biology
2.4.1 Generative Models
2.4.2 Generative Adversarial Networks (GANs)
2.4.2.1 Variational Autoencoders (VAEs)
2.4.2.2 Normalizing Flows
2.4.2.3 Autoregressive Models
2.4.2.4 Evolutionary Generative Models
2.4.3 Design Optimization
2.4.3.1 Evolutionary Algorithms (e.g., Genetic Algorithms, Evolutionary Strategies)
2.4.3.1.1 Genetic Algorithms (GAs)
2.4.3.1.2 Evolutionary Strategies (ES)
2.4.3.2 Reinforcement Learning
2.4.3.3 Multi-Objective Optimization
2.4.3.4 Bayesian Optimization
2.4.4 Computational Biology
2.4.4.1 Molecular Dynamics Simulations
2.4.4.2 Quantum Mechanical Calculations
2.4.4.3 Systems Biology Modeling
2.4.4.4 Metabolic Engineering Modeling
2.4.5 Data-Driven Approaches
2.4.5.1 Machine Learning
2.4.5.2 Graph Neural Networks
2.4.5.3 Unsupervised Learning
2.4.5.4 Active Learning and Bayesian Optimization
2.4.6 Agent-Based Modeling
2.4.7 Hybrid Approaches
2.5 Feedstocks
2.5.1 C1 feedstocks
2.5.1.1 Advantages
2.5.1.2 Pathways
2.5.1.3 Challenges
2.5.1.4 Non-methane C1 feedstocks
2.5.1.5 Gas fermentation
2.5.2 C2 feedstocks
2.5.3 Biological conversion of CO2
2.5.4 Food processing wastes
2.5.5 Lignocellulosic biomass
2.5.6 Methane
2.5.7 Municipal solid wastes
2.5.8 Plastic wastes
2.5.9 Plant oils
2.5.10 Starch
2.5.11 Sugars
2.5.12 Used cooking oils
2.5.13 Carbon capture
2.5.14 Green hydrogen production
2.5.15 Blue hydrogen production
2.6 Blue biotechnology (Marine biotechnology)
2.6.1 Cyanobacteria
2.6.2 Macroalgae
2.6.3 Companies
3 MARKET ANALYSIS
3.1 Market trends
3.1.1 Demand for biobased products
3.1.2 Government regulation
3.1.3 Costs
3.1.4 Carbon taxes
3.2 Industry challenges and constraints
3.2.1 Costs
3.2.1.1 Oil prices
3.2.1.2 Green Premium
3.2.1.3 Cell Factory Cost
3.3 White biotechnology in the bioeconomy
3.4 SWOT analysis
3.5 Market map
3.6 Key market players and competitive landscape
3.7 Regulations
3.7.1 United States
3.7.2 European Union
3.7.3 International
3.7.4 Specific Regulations and Guidelines
3.8 Main end-use markets
3.8.1 Biofuels
3.8.1.1 Market supply chain
3.8.1.2 Solid Biofuels
3.8.1.3 Liquid Biofuels
3.8.1.4 Gaseous Biofuels
3.8.1.5 Conventional Biofuels
3.8.1.6 Next-generation Biofuels
3.8.1.7 Feedstocks
3.8.1.7.1 First-generation (1-G)
3.8.1.7.2 Second-generation (2-G)
3.8.1.7.2.1 Lignocellulosic wastes and residues
3.8.1.7.2.2 Biorefinery lignin
3.8.1.7.3 Third-generation (3-G)
3.8.1.7.3.1 Algal biofuels
3.8.1.7.3.1.1 Properties
3.8.1.7.3.1.2 Advantages
3.8.1.7.4 Fourth-generation (4-G)
3.8.1.7.5 Energy crops
3.8.1.7.6 Agricultural residues
3.8.1.7.7 Manure, sewage sludge and organic waste
3.8.1.7.8 Forestry and wood waste
3.8.1.7.9 Feedstock costs
3.8.1.8 Bioethanol
3.8.1.8.1 Ethanol to jet fuel technology
3.8.1.8.2 Methanol from pulp & paper production
3.8.1.8.3 Sulfite spent liquor fermentation
3.8.1.8.4 Gasification
3.8.1.8.4.1 Biomass gasification and syngas fermentation
3.8.1.8.4.2 Biomass gasification and syngas thermochemical conversion
3.8.1.8.5 CO2 capture and alcohol synthesis
3.8.1.8.6 Biomass hydrolysis and fermentation
3.8.1.8.7 Separate hydrolysis and fermentation
3.8.1.8.7.1 Simultaneous saccharification and fermentation (SSF)
3.8.1.8.7.2 Pre-hydrolysis and simultaneous saccharification and fermentation (PSSF)
3.8.1.8.7.3 Simultaneous saccharification and co-fermentation (SSCF)
3.8.1.8.7.4 Direct conversion (consolidated bioprocessing) (CBP)
3.8.1.9 Biodiesel
3.8.1.10 Biogas
3.8.1.10.1 Biomethane
3.8.1.10.2 Feedstocks
3.8.1.10.3 Anaerobic digestion
3.8.1.11 Renewable diesel
3.8.1.12 Biojet fuel
3.8.1.13 Algal biofuels (blue biotech)
3.8.1.13.1 Conversion pathways
3.8.1.13.2 Market challenges
3.8.1.13.3 Prices
3.8.1.13.4 Producers
3.8.1.14 Biohydrogen
3.8.1.14.1 Biological Conversion Routes
3.8.1.14.1.1 Bio-photochemical Reaction
3.8.1.14.1.2 Fermentation and Anaerobic Digestion
3.8.1.15 Biobutanol
3.8.1.16 Bio-based methanol
3.8.1.16.1 Anaerobic digestion
3.8.1.16.2 Biomass gasification
3.8.1.16.3 Power to Methane
3.8.1.17 Bioisoprene
3.8.1.18 Fatty Acid Esters
3.8.2 Bio-based chemicals
3.8.2.1 Market supply chain
3.8.2.2 Acetic acid
3.8.2.3 Adipic acid
3.8.2.4 Aldehydes
3.8.2.5 Acrylic acid
3.8.2.6 Bacterial cellulose
3.8.2.7 1,4-Butanediol (BDO)
3.8.2.8 Bio-DME
3.8.2.9 Dodecanedioic acid (DDDA)
3.8.2.10 Ethylene
3.8.2.11 3-Hydroxypropionic acid (3-HP)
3.8.2.12 1,3-Propanediol (1,3-PDO)
3.8.2.13 Itaconic acid
3.8.2.14 Lactic acid (D-LA)
3.8.2.15 1,5-diaminopentane (DA5)
3.8.2.16 Tetrahydrofuran (THF)
3.8.2.17 Malonic acid
3.8.2.18 Monoethylene glycol (MEG)
3.8.2.19 Propylene
3.8.2.20 Succinic acid (SA)
3.8.2.21 Triglycerides
3.8.2.22 Enzymes
3.8.2.23 Vitamins
3.8.2.24 Antibiotics
3.8.3 Bioplastics and Biopolymers
3.8.3.1 Bioplastics via white biotechnology
3.8.3.2 Biobased polymers from monosaccharides
3.8.3.3 Market supply chain
3.8.3.4 Lactic Acid and Polylactic Acid (PLA)
3.8.3.4.1 Lactic Acid (C3H6O3)
3.8.3.4.2 Industrial production of lactic acid
3.8.3.4.3 Engineering Yeast Strains for Lactic Acid Production
3.8.3.4.4 Polylactic acid (PLA) production
3.8.3.5 Succinic Acid
3.8.3.5.1 Biobased succinic acid production
3.8.3.5.2 PBS
3.8.3.6 2,5-furandicarboxylic acid (FDCA)
3.8.3.6.1 Monomer Production
3.8.3.7 Polyethylene Furanoate (PEF)
3.8.3.8 C6 monomers
3.8.3.9 Sebacic Acid
3.8.3.10 Dodecanedioic Acid
3.8.3.11 1,5-Pentanediamine (PDA)
3.8.3.12 1,3-Butadiene
3.8.3.13 Isoprene
3.8.3.14 Isobutene (Isobutylene)
3.8.3.15 PHAs
3.8.3.15.1 Production of PHAs
3.8.3.15.2 PHB, PHBV, and P(3HB-co-4HB)
3.8.3.15.3 Commercial PHA landscape
3.8.3.15.4 Short and medium chain-length PHAs
3.8.3.15.5 Economic viability of PHA production
3.8.3.15.6 Risks
3.8.3.15.7 Production scale
3.8.3.15.8 PHA production landscape
3.8.3.15.9 Commercially available PHAs
3.8.3.16 Bio-PET
3.8.3.17 Starch blends
3.8.3.18 Protein-based bioplastics
3.8.4 Bioremediation
3.8.5 Biocatalysis
3.8.5.1 Biotransformations
3.8.5.2 Cascade biocatalysis
3.8.5.3 Co-factor recycling
3.8.5.4 Immobilization
3.8.6 Food and Nutraceutical Ingredients
3.8.6.1 Market supply chain
3.8.6.2 Alternative Proteins
3.8.6.3 Natural Sweeteners
3.8.6.4 Natural Flavors and Fragrances
3.8.6.5 Texturants and Thickeners
3.8.6.6 Nutraceuticals and Supplements
3.8.7 Agricultural biotechnology
3.8.7.1 Market supply chain
3.8.7.2 Biofertilizers
3.8.7.2.1 Overview
3.8.7.2.2 Companies
3.8.7.3 Biopesticides
3.8.7.3.1 Overview
3.8.7.3.2 Companies
3.8.7.4 Biostimulants
3.8.7.4.1 Overview
3.8.7.4.2 Companies
3.8.7.5 Crop Biotechnology
3.8.7.5.1 Genetic engineering
3.8.7.5.2 Genome editing
3.8.7.5.3 Companies
3.8.8 Textiles
3.8.8.1 Market supply chain
3.8.8.2 Bio-Based Fibers
3.8.8.2.1 Lyocell
3.8.8.2.2 Bacterial cellulose
3.8.8.2.3 Algae textiles
3.8.8.3 Spider silk
3.8.8.4 Collagen-derived textiles
3.8.8.5 Recombinant Materials
3.8.8.6 Sustainable Processing
3.8.9 Consumer goods
3.8.9.1 Market supply chain
3.8.9.2 White biotechnology in consumer goods
3.8.10 Biopharmaceuticals
3.8.10.1 Market supply chain
3.8.10.2 Market overview for white biotechnology
3.8.11 Cosmetics
3.8.11.1 Market supply chain
3.8.11.2 Market overview for white biotechnology
3.8.12 Surfactants and detergents
3.8.12.1 Market supply chain
3.8.12.2 Market overview for white biotechnology
3.8.13 Construction materials
3.8.13.1 Market supply chain
3.8.13.2 Biocement
3.8.13.3 Mycelium materials
3.9 Global market revenues 2018-2035
3.9.1 By molecule
3.9.2 By market
3.9.3 By region
3.10 Future Market Outlook
4 COMPANY PROFILES 313 (396 company profiles)
5 APPENDIX
5.1 Research methodology
5.2 Acronyms
5.3 Glossary of Terms
6 REFERENCES
List of Tables
Table 1. Biotechnology "colours".
Table 2. Differences between white biotechnology and conventional processes.
Table 3. Application areas for white biotechnology.
Table 4. Advantages of white biotechnology.
Table 5. Routes for carbon capture in white biotechnology.
Table 6. Molecules produced through industrial biomanufacturing.
Table 7. Commonly used bacterial hosts for white biotechnology production.
Table 8. Commonly used yeast hosts for white biotech production.
Table 9. Examples of fungal hosts used in white biotechnology processes.
Table 10. Examples of marine organisms as hosts for white biotechnology applications.
Table 11. Common microbial hosts used for enzyme production in white biotechnology.
Table 12. Photosynthetic microorganisms used as production hosts in white biotechnology
Table 13. Biomanufacturing processes utilized in white biotechnology.
Table 14. Continuous vs batch biomanufacturing
Table 15. Key fermentation parameters in batch vs continuous biomanufacturing processes.
Table 16. Microorganisms in Biomanufacturing Processes.
Table 17. Pharmaceutical Industry
Table 18. Biofuel Industry
Table 19. Industrial Enzyme Production
Table 20. Food and Beverage Industry
Table 21. Non-Model Organisms for White Biotechnology
Table 22. Machine Learning Applications in Biomanufacturing
Table 23. Hybrid Biotechnological-Chemical Approaches
Table 24. Core stages - Design, Build and Test.
Table 25. Synthetic Biology: Drivers and Barriers for Adoption
Table 26. Products and applications enabled by synthetic biology.
Table 27. Engineered proteins in industrial applications.
Table 29. Cell-free versus cell-based systems
Table 30. Technology Readiness Assessment
Table 31. Machine Learning Based Improvements for Biomanufacturing.
Table 32. AI-driven Fermentation Platform Companies
Table 33. White biotechnology fermentation processes.
Table 34. Alternative feedstocks for white biotechnology
Table 35. Products from C1 feedstocks in white biotechnology.
Table 36. C2 Feedstock Products.
Table 37. CO2 derived products via biological conversion-applications, advantages and disadvantages.
Table 38. Production capacities of biorefinery lignin producers.
Table 39. Common starch sources that can be used as feedstocks for producing biochemicals.
Table 40. Routes for carbon capture in white biotechnology.
Table 41. Biomass processes summary, process description and TRL.
Table 42. Pathways for hydrogen production from biomass.
Table 43. Overview of alginate-description, properties, application and market size.
Table 44. Blue biotechnology companies.
Table 45. Market trends and drivers in white biotechnology.
Table 46. Industry challenges and restraints in white biotechnology.
Table 47. White biotechnology key application sectors and products.
Table 48. Comparison of biofuels.
Table 49. Categories and examples of solid biofuel.
Table 50. Comparison of biofuels and e-fuels to fossil and electricity.
Table 51. Classification of biomass feedstock.
Table 52. Biorefinery feedstocks.
Table 53. Feedstock conversion pathways.
Table 54. First-Generation Feedstocks.
Table 55. Lignocellulosic ethanol plants and capacities.
Table 56. Comparison of pulping and biorefinery lignins.
Table 57. Commercial and pre-commercial biorefinery lignin production facilities and processes
Table 58. Operating and planned lignocellulosic biorefineries and industrial flue gas-to-ethanol.
Table 59. Properties of microalgae and macroalgae.
Table 60. Yield of algae and other biodiesel crops.
Table 61.  Processes in bioethanol production.
Table 62. Microorganisms used in CBP for ethanol production from biomass lignocellulosic.
Table 63. Biodiesel by generation.
Table 64. Biodiesel production techniques.
Table 65. Biofuel production cost from the biomass pyrolysis process.
Table 66. Biogas feedstocks.
Table 67. Advantages and disadvantages of Bio-aviation fuel.
Table 68. Production pathways for Bio-aviation fuel.
Table 69. Current and announced Bio-aviation fuel facilities and capacities.
Table 70. Algae-derived biofuel producers.
Table 71. Markets and applications for biohydrogen.
Table 72. Comparison of different Bio-H2 production pathways.
Table 73. Properties of petrol and biobutanol.
Table 74. Comparison of biogas, biomethane and natural gas.
Table 75. Applications of bio-based caprolactam.
Table 76. Applications of bio-based acrylic acid.
Table 77. Applications of bio-based 1,4-Butanediol (BDO).
Table 78. Applications of bio-based ethylene.
Table 79. Biobased feedstock sources for 3-HP.
Table 80. Applications of 3-HP.
Table 81. Applications of bio-based 1,3-Propanediol (1,3-PDO).
Table 82. Biobased feedstock sources for itaconic acid.
Table 83. Applications of bio-based itaconic acid.
Table 84. Biobased feedstocks that can be used to produce 1,5-diaminopentane (DA5).
Table 85. Applications of DN5.
Table 86. Applications of bio-based Tetrahydrofuran (THF).
Table 87. Markets and applications for malonic acid.
Table 88. Biobased feedstock sources for MEG.
Table 89. Applications of bio-based MEG.
Table 90. Applications of bio-based propylene.
Table 91. Biobased feedstock sources for Succinic acid.
Table 92. Applications of succinic acid.
Table 94. Bioplastics and bioplastic precursors synthesized via white biotechnology processes .
Table 95. Optimal Lactic Acid Bacteria Strains for Fermentation.
Table 96. Polylactic acid (PLA) market analysis-manufacture, advantages, disadvantages and applications.
Table 97. PLA producers and production capacities.
Table 98. Molecules for Other Biobased Synthetic Polymers.
Table 99. Biosynthetic Pathways to Polyamides
Table 100. Biosynthetic Pathways to PHAs
Table 101. Key Commercial PHAs and Microstructures.
Table 102. Types of PHAs
Table 103. Material Properties of Commercial PHAs
Table 104. Property Comparison Across Applications
Table 105. Applications of PHAs.
Table 106. Application-Specific Economic Analysis
Table 107. Polyhydroxyalkanoate (PHA) extraction methods.
Table 108. Commercially available PHAs.
Table 109. Types of protein based-bioplastics, applications and companies.
Table 110. Applications of white biotechnology in bioremediation and environmental remediation.
Table 111. Companies developing fermentation-derived food.
Table 112. Biofertilizer companies.
Table 113. Biopesticides companies.
Table 114. Biostimulants companies.
Table 115. Crop biotechnology companies.
Table 116. White biotechnology applications in consumer goods.
Table 117. Pharmaceutical applications of white biotechnology.
Table 118. Applications of white biotechnology in the cosmetics industry.
Table 119. Sustainable biomanufacturing of surfactants and detergents.
Table 120. Global revenues for white biotechnology, by molecule, 2018-2035 (Billion USD).
Table 121. Global revenues for white biotechnology, by market, 2018-2035 (Billion USD).
Table 122. Global revenues for white biotechnology, by region, 2018-2035 (Billion USD).
Table 123. White biotechnology Glossary of Acronyms.
Table 124. White biotechnology Glossary of Terms.
List of Figures
Figure 1. CRISPR/Cas9 & Targeted Genome Editing.
Figure 2. Genetic Circuit-Assisted Smart Microbial Engineering.
Figure 3. Cell-free and cell-based protein synthesis systems.
Figure 4. Microbial Chassis Development for Natural Product Biosynthesis.
Figure 5. The design-make-test-learn loop of generative biology.
Figure 6. LanzaTech gas-fermentation process.
Figure 7. Schematic of biological CO2 conversion into e-fuels.
Figure 8. Overview of biogas utilization.
Figure 9. Biogas and biomethane pathways.
Figure 10. Schematic overview of anaerobic digestion process for biomethane production.
Figure 11. BLOOM masterbatch from Algix.
Figure 12. SWOT analysis: white biotechnology.
Figure 13. Market map: white biotechnology.
Figure 14. Biofuels market supply chain.
Figure 15. Schematic of a biorefinery for production of carriers and chemicals.
Figure 16. Hydrolytic lignin powder.
Figure 17. Range of biomass cost by feedstock type.
Figure 18. Overview of biogas utilization.
Figure 19. Biogas and biomethane pathways.
Figure 20. Schematic overview of anaerobic digestion process for biomethane production.
Figure 21. Algal biomass conversion process for biofuel production.
Figure 22. Pathways for algal biomass conversion to biofuels.
Figure 23. Biobutanol production route.
Figure 24. Renewable Methanol Production Processes from Different Feedstocks.
Figure 25. Production of biomethane through anaerobic digestion and upgrading.
Figure 26. Production of biomethane through biomass gasification and methanation.
Figure 27. Production of biomethane through the Power to methane process.
Figure 28. Bio-based chemicals market supply chain.
Figure 29. Overview of Toray process.
Figure 30. Bacterial nanocellulose shapes
Figure 31. Bioplastics and biopolymers market supply chain.
Figure 32. Food and Nutraceutical Ingredients market supply chain.
Figure 33. Agricultural biotechnology market supply chain.
Figure 34. Bio-textiles market supply chain.
Figure 35. AlgiKicks sneaker, made with the Algiknit biopolymer gel.
Figure 36. Biobased consumer goods market supply chain.
Figure 37. Biopharmaceuticals market supply chain.
Figure 38. Biobased cosmetics market supply chain.
Figure 39. Surfactants and detergents market supply chain.
Figure 40. Biobased construction materials market supply chain.
Figure 41. BioMason cement.
Figure 42. Microalgae based biocement masonry bloc.
Figure 43. Typical structure of mycelium-based foam.
Figure 44. Commercial mycelium composite construction materials.
Figure 45. Global revenues for white biotechnology, by market, 2018-2035 (Billion USD).
Figure 46. Global revenues for white biotechnology, by region, 2018-2035 (Billion USD).
Figure 47. Algiknit yarn.
Figure 48. ALGIECEL PhotoBioReactor.
Figure 49. Jelly-like seaweed-based nanocellulose hydrogel.
Figure 50. BIOLO e-commerce mailer bag made from PHA.
Figure 51. Domsjö process.
Figure 52. Mushroom leather.
Figure 53. PHA production process.
Figure 54. Light Bio Bioluminescent plants.
Figure 55. Lignin gel.
Figure 56. BioFlex process.
Figure 57. TransLeather.
Figure 58. Reishi.
Figure 59. Compostable water pod.
Figure 60. Precision Photosynthesis™ technology.
Figure 61. Enfinity cellulosic ethanol technology process.
Figure 62. Fabric consisting of 70 per cent wool and 30 per cent Qmilk.
Figure 63. Lyocell process.
Figure 64. Spider silk production.
Figure 65. Corbion FDCA production process.
Figure 66. UPM biorefinery process.
Figure 67. The Proesa® Process.
Figure 68. XtalPi’s automated and robot-run workstations.

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